protein-tools-mcp

Overview Schema Source Related Servers Discussions Admin

propka_summary

Parse PROPKA .pka output for pI, pKa extremes, residue counts, and protonation flags (HIS near pH 7, raised acids) to guide pdb2gmx protonation decisions.

Instructions

Parse a PROPKA .pka output: pI, per-residue-type counts, pKa extremes, and protonation-state concerns (HIS near pH 7, raised acids, CYS 99.99 disulfide markers) - exactly the decisions pdb2gmx protonation needs.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "pka_path": "<pka_path>"
    },
    "name": "propka_summary"
  }
}

Input Schema

Name	Required	Description	Default
`pka_path`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 20, 2026

TDQS

A3.5/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses what gets surfaced from the .pka file (HIS near pH 7, raised acids, CYS 99.99 disulfide markers), which is real context, but says nothing about read-only nature, missing/malformed file handling, or output size.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One dense, front-loaded sentence that leads with the verb and resource, then layers the extracted content and the downstream rationale. No filler, though the parenthetical list makes it slightly heavy for a single sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value enumeration is a bonus rather than a necessity, and the description still tells the agent what to expect. With no annotations, a brief note on read-only behavior or file prerequisites would close the remaining gap, but the definition is adequate for a one-parameter parser.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is one parameter, pka_path, and the schema gives it 0% description coverage. The description references the '.pka output' implicitly but adds no path-format, required-extension, or validity detail, so it neither compensates for the coverage gap nor drops below baseline for a self-evident single file path.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (parse) and resource (PROPKA .pka output) and enumerates the exact quantities extracted (pI, residue-type counts, pKa extremes, protonation-state flags). It is clearly distinguishable from the other *_summary siblings by content, though it never names them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The trailing clause 'exactly the decisions pdb2gmx protonation needs' implies the downstream use case, but there is no explicit when-to-use/when-not statement and no named alternative among the many sibling summary tools. Usage is inferable rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.